About Our Group

Our research focuses on methods to enable engineering design and analysis with intrusive and non-intrusive data-driven surrogate models.

Simulating parameterized systems of equations is ubiquitous in science and engineering. It is often the case that solving such systems with high level of accuracy is a computationally intensive process. For many-query analyses such as uncertainty quantification and optimization, reduced models are required to make the analysis tractable. Model reduction is a broad and active field. Several techniques exist, but there is no such thing as “one method to rule them all”.

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